• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.171-178
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• 2008

Foreign word transliterations are not consistently used in documents, which hinders retrieving some important relevant documents in exact term matching information retrieval systems. In this paper, a meta search method is proposed, which expands and refines relevant variant queries from an original input foreign word transliteration query to retrieve the more relevant documents. The method firstly expands a transliteration query to the variants using a statistical method. Secondly the method selects the valid variants: it queries each variant to the retrieval systems beforehand and checks the validity of each variant by counting the number of appearance of the variant in the retrieved document and calculating the similarity of the context of the variant. Experiment result showed that querying with the variants produced at the first step, which is a base method of the test, performed 38% in average F measure, and querying with the refined variants at the second step, which is a proposed method, significantly improved the performance to 81% in average F measure.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.62-65
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• 2006

XML은 웹 상에서 데이터의 표현과 교환을 위한 표준이다. XQuery는 XML 질의를 위한 W3C 표준으로서 XML 문서를 효율적으로 검색하기 위해서 W3C에서 제안한 표준질의어이다. XQuery가 등장하면서, 이를 빠르게 처리하기 위한 연구가 많이 진행 중이며, 이 연구 중 한 분야는 XQuery 질의를 정제하는 것이다. 사용자에 따라 다양하게 작성되는 XQuery 질의들은 정제되어 있지 않을 수 있다. 질의의 불필요한 연산이나 표현을 제거하여 간결하게 만드는 것은 질의를 효율적으로 처리하게 하여 성능을 향상시키는데 도움을 준다. 이에 대한 이전의 연구들은 XML 데이터의 저장구조나 시스템에 의존적인 질의 정제방법을 사용하므로 이들 방법을 일반적인 XQuery 질의 정제로 볼 수는 없다. 그러나 우리의 정제방법은 XQuery 질의를 기반으로 하여 일반적인 상황에서도 질의의 정제가 가능하므로 XQuery를 입력으로 하는 다른 시스템에서 우리의 방법으로 입력 질의를 정제하여 효율적으로 질의를 처리할 수 있다. 본 논문에서는 XQuery 질의를 효율적으로 처리하기 위하여 두가지 정제방법을 제안한다. 첫째는 불필요한 연산이나 표현을 제거하는 방법이고, 둘째는 질의의 순서를 재배치하는 방법이다. 이 방법들을 통하여 질의를 보다 빠르고 효율적으로 처리하도록 한다. 끝으로, 우리는 성능평가를 통하여 우리의 정제방법의 효율성을 입증한다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.14 no.1
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• pp.219-230
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• 2003

The purpose of this study is to improve of retrieval effectiveness to clustered and filtered document through query expansion. The result of this research prove that extended queries and documents, information in encyclopedia, clustering and filtering techniques are effective to promote retrieval effectiveness.

• Annual Conference on Human and Language Technology
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• 2003.10d
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• pp.95-100
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• 2003

본 논문에서는 현실 세계가 가지고 있는 지식이 어느 정도 체계적으로 정제되어 있는 국어사전, 백과사전 등을 중심으로, Hybrid Method를 이용한 통계(Statistics)기반 지식베이스와 어휘분류(Lexicon Classification)기반 지식베이스를 효율적으로 구축하여 질의응답시스템에 활용한다. 또한 특정한 문서를 보여주는 일반적인 질의응답시스템과는 달리, 이러한 지식베이스를 이용하여 사용자에게 정확한 개념어(정답어)를 습득하게끔 해주고, 사용자의 인지 체계 속에 어렴풋이 내포되어 있는 개념적 지식을 더욱더 표면적으로 확장해 나갈 수 있는 질의응답시스템을 구축하는 방안을 제시한다.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.4
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• pp.149-154
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• 2014

A user should pick up relevant answers by himself from various search results when using user participation question answering community like Knowledge-iN. If refined answers are automatically provided, usability of question answering community must be improved. This paper divides questions in Q&A documents into 4 types(word, list, graph and text), then proposes summarizing methods for each question type using document statistics. Summarized answers for word, list and text type are obtained by question clustering and calculating scores for words using frequency, proximity and confidence of answers. Answers for graph type is shown by extracting user opinion from answers.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.123-124
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• 2014

무선 센서 네트워크는 센서들을 근거리 네트워크로 연결하여 사용자와 현장의 정보를 실시간으로 연결해 주는 매개체 역할을 한다. 이러한 무선 센서 네트워크는 기존의 컴퓨팅 시스템과는 달리 제한된 자원과 환경 속에서 동작을 해야 하고, 접근이 힘든 곳이나 지속적인 관리가 필요한 지역에서 효율적으로 사용된다. 본 논문에서는 무선 센서네트워크의 제한된 자원 속에서 불완전 스트림 데이터를 효율적으로 정제하고 처리하여 빠르고 정확한 질의어 처리가 가능한 질의 시스템을 제안하였다.

• Journal of the Korean Society for information Management
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• v.19 no.3
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• pp.111-122
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• 2002

In order to investigate information seeking behavior of web search users, this study analyzes transaction logs posed by users of NAVER, a major Korean Internet search service. We present a session definition method for Web transaction log analysis, a way of cleaning original logs and a query classification method. We also propose a query term definition method that is necessary for Korean Web transaction log analysis. It is expected that this study could contribute to the development and implementation of more effective Web search systems and services.

• Korean Journal of Food Science and Technology
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• v.4 no.4
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• pp.252-258
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• 1972

Methods of separating yeast cells from oil-water-cell emulsion and subsequent purification of the recovered yeast have been studied. In addition, the results of preliminary feeding experiments in which a yeast grown on gas oil was incorporated into chick rations are reported. According to the present study, it appears that the recovery of the yeasts would be easier at pH 9, since the emulsion is relatively more unstable. A class of surface active agent at a concentration of 0.3% was found to facilitate the separation of the yeast from the emulsion. The use of electrolytes such as NaCl and KCl were found to be most effective in breaking the emulsion. Solvent treatment using iso-propyl alcohol and its azeotropic mixture with hexane at $58^{\circ}C$ are particularly suitable for purification of the yeast. In the feeding experiment it was found that 5 percent of the fishmeal in the control ration could be replaced by the yeast with no adverse effect on performance. However, when 8 percent of the fish meal in the control ration was replaced by the yeast, some effect on live-weight gain of the chicks was observed.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.